Multiple camera tunnel systems can offer very high read rates when they are properly configured and maintained. In order to ensure that such camera tunnel systems are properly functioning, the performance of the camera in such systems needs be measured and compared to some standard. Currently such camera quality measurements are conducted by human operators and as such they are very dependent on variance from one operator to the next. The measurement metrics for the performance quality of the camera in such tunnel systems tends to include a very large operator influence. Such an operator-based influence adversely impacts the consistency of the measurement of such metrics over time and across various systems.
High speed camera tunnel systems can offer advances in barcode reading performance. Such systems can offer the use of package images for advanced features not possible with current laser-based scanning systems. However, in order to harness the full potential of high speed camera tunnel systems their image acquisition capabilities need to be well-maintained.
Current methods of evaluating a camera tunnel setup involve manually analyzing saved images that include a test pattern. For example, current image analysis software programs (e.g., Photo Shop) can be used to inspect various features of the test pattern image. This inspection requires a skilled operator and does not ensure consistency, especially across various systems, because in each case the particular operator follows a series of steps or prompts, each of which is subjective and subject to variations among different operators and systems. The values determined from this series of manual, subjective operations thus typically will vary among systems and their operators. The subjective nature of using the operator to evaluate an image fails to meet the need for a consistent, repeatable and verifiable evaluation of the system. Additionally, even if an entire cadre of skilled and consistent operators were available, the need for a skilled operator limits the value of such an operator-based system.
Consequently, current manual image analysis techniques do not offer a consistent, repeatable, objective and verifiable measure of the camera system's performance. The large scale deployment and broad acceptance of such systems require an image analysis solution that does not requires manual operation by specially trained technicians.
There is therefore a need for a system and a method to measure the quality of the performance of a camera system that does not suffer from the above-mentioned shortcomings.